Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "68"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 68 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 31 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 29 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 68, Node N03:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459846 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 1.668357 49.428107 -0.105368 46.964832 -0.362105 20.767224 0.235791 11.505540 0.8527 0.0292 0.5599 3.184062 1.158829
2459845 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 4.156174 44.773307 0.442027 58.100232 0.013559 15.905683 1.217242 10.233780 0.7338 0.0383 0.4948 3.638665 0.823177
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 33.503617 11.608340 23.850192 44.742875 3.345283 9.178670 11.064367 44.206295 0.0254 0.0202 0.0025 nan nan
2459843 digital_ok 100.00% 0.66% 100.00% 0.00% 100.00% 0.00% 5.469558 44.830321 1.609231 28.789323 0.685699 68.962224 1.931203 8.088528 0.7437 0.0310 0.4697 3.562063 1.216694
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 71.117882 65.005327 15.515848 16.260656 5.023532 9.282003 17.090199 24.399617 0.0227 0.0198 0.0016 nan nan
2459839 digital_ok 100.00% - - - - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459838 digital_ok 100.00% 0.00% 100.00% 0.00% 100.00% 0.00% 3.107781 41.614338 2.624121 33.473430 1.040692 28.055644 -0.171544 6.940325 0.7625 0.0374 0.4582 5.775157 1.251853
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0333 0.0328 0.0022 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - 1.308012 -0.932991 0.054261 3.882416 0.356295 3.824567 0.548759 3.075567 0.0322 0.0313 0.0015 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 8.847365 8.957556 7.801666 7.042747 1.547263 2.835400 8.723880 10.046868 0.0250 0.0246 0.0011 nan nan
2459832 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.755629 0.984665 1.895252 0.435833 1.917805 2.253015 0.005353 2.261437 0.8091 0.5700 0.5466 1.805013 1.801631
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - 18.528172 16.590712 39.849140 42.728581 2.057609 3.137750 16.485113 21.579004 0.0229 0.0212 0.0014 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.280798 1.054715 2.943337 1.643151 2.649919 5.132762 0.348670 1.649101 0.8098 0.5869 0.5218 4.815321 4.530988
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.596359 2.042374 3.085392 4.858339 14.403664 17.915248 3.449397 11.330341 0.7650 0.6890 0.3754 20.439425 17.340923
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.942555 1.505835 -0.260115 9.322643 1.699308 5.968515 0.564285 5.522492 0.8096 0.5855 0.5113 4.504674 4.762824
2459827 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.724386 1.406564 0.202729 10.466520 0.388498 3.554953 0.328102 -0.299157 0.7743 0.6928 0.3781 8.922033 9.508836
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.567081 1.027846 0.656463 8.919044 1.873120 5.339033 -0.157081 0.712369 0.8080 0.6059 0.4916 6.071136 6.500946
2459825 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.601895 0.706287 -0.020976 3.269602 0.952072 4.956718 -0.486074 1.119662 0.8110 0.6258 0.4869 7.220216 7.799067
2459824 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.393584 1.411057 -0.389631 3.378787 -0.053450 0.926914 0.069960 0.740074 0.7464 0.7601 0.3179 1.912970 1.974894
2459823 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.486251 1.711329 1.121924 2.410308 0.868924 1.896999 -0.843725 1.057194 0.7840 0.6792 0.4244 1.989428 2.039854
2459822 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.637138 0.898933 0.425462 3.304682 1.375359 4.000856 0.501032 0.814695 0.8142 0.6528 0.4777 6.475642 7.760546
2459821 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.045337 0.588888 0.126886 3.680864 1.333265 4.191372 0.460960 2.197101 0.8154 0.6778 0.4655 4.665535 4.559945
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.192410 1.184471 -0.059118 2.677139 3.110297 17.175543 0.601494 1.089188 0.7884 0.7257 0.3782 5.042608 4.876040
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 44.74% 0.653606 0.583511 -0.080662 -0.100655 -0.185776 1.329653 -0.229239 -0.422309 0.8305 0.7194 0.4583 2.753654 3.421898
2459816 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.171532 0.953705 -0.083661 -0.154167 0.683593 2.070924 -0.117763 -0.458911 0.8485 0.6317 0.5558 1.928593 1.681280
2459815 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 7.89% 0.938687 0.637395 0.198746 -0.536887 0.641127 1.480487 -0.418399 -0.362734 0.8274 0.7318 0.4648 2.003624 1.864972
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.805328 2.656853 -0.361732 -0.046432 3.568880 8.794587 1.030517 0.621377 0.8099 0.7748 0.3625 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 68: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Shape 49.428107 1.668357 49.428107 -0.105368 46.964832 -0.362105 20.767224 0.235791 11.505540

Antenna 68: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 58.100232 44.773307 4.156174 58.100232 0.442027 15.905683 0.013559 10.233780 1.217242

Antenna 68: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 44.742875 33.503617 11.608340 23.850192 44.742875 3.345283 9.178670 11.064367 44.206295

Antenna 68: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 68.962224 44.830321 5.469558 28.789323 1.609231 68.962224 0.685699 8.088528 1.931203

Antenna 68: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok ee Shape 71.117882 71.117882 65.005327 15.515848 16.260656 5.023532 9.282003 17.090199 24.399617

Antenna 68: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 68: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Shape 41.614338 41.614338 3.107781 33.473430 2.624121 28.055644 1.040692 6.940325 -0.171544

Antenna 68: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 3.882416 -0.932991 1.308012 3.882416 0.054261 3.824567 0.356295 3.075567 0.548759

Antenna 68: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Discontinuties 10.046868 8.957556 8.847365 7.042747 7.801666 2.835400 1.547263 10.046868 8.723880

Antenna 68: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Discontinuties 2.261437 1.755629 0.984665 1.895252 0.435833 1.917805 2.253015 0.005353 2.261437

Antenna 68: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 42.728581 18.528172 16.590712 39.849140 42.728581 2.057609 3.137750 16.485113 21.579004

Antenna 68: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 5.132762 2.280798 1.054715 2.943337 1.643151 2.649919 5.132762 0.348670 1.649101

Antenna 68: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 17.915248 2.042374 3.596359 4.858339 3.085392 17.915248 14.403664 11.330341 3.449397

Antenna 68: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 9.322643 1.505835 1.942555 9.322643 -0.260115 5.968515 1.699308 5.522492 0.564285

Antenna 68: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 10.466520 2.724386 1.406564 0.202729 10.466520 0.388498 3.554953 0.328102 -0.299157

Antenna 68: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 8.919044 1.027846 1.567081 8.919044 0.656463 5.339033 1.873120 0.712369 -0.157081

Antenna 68: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 4.956718 0.706287 1.601895 3.269602 -0.020976 4.956718 0.952072 1.119662 -0.486074

Antenna 68: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 3.378787 2.393584 1.411057 -0.389631 3.378787 -0.053450 0.926914 0.069960 0.740074

Antenna 68: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Power 2.410308 1.711329 1.486251 2.410308 1.121924 1.896999 0.868924 1.057194 -0.843725

Antenna 68: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 4.000856 1.637138 0.898933 0.425462 3.304682 1.375359 4.000856 0.501032 0.814695

Antenna 68: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 4.191372 0.588888 1.045337 3.680864 0.126886 4.191372 1.333265 2.197101 0.460960

Antenna 68: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 17.175543 3.192410 1.184471 -0.059118 2.677139 3.110297 17.175543 0.601494 1.089188

Antenna 68: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 1.329653 0.653606 0.583511 -0.080662 -0.100655 -0.185776 1.329653 -0.229239 -0.422309

Antenna 68: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 2.070924 0.953705 1.171532 -0.154167 -0.083661 2.070924 0.683593 -0.458911 -0.117763

Antenna 68: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 1.480487 0.637395 0.938687 -0.536887 0.198746 1.480487 0.641127 -0.362734 -0.418399

Antenna 68: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 68: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
68 N03 digital_ok nn Temporal Variability 8.794587 2.656853 3.805328 -0.046432 -0.361732 8.794587 3.568880 0.621377 1.030517
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